Enhanced K-means re-clustering over dynamic networks

作者：

Highlights：

• Introducing a new enhanced K-Means clustering algorithm for dynamic clustering.

• Detecting the nodes with the potential of changing their clusters after each change.

• Completely local calculations during the dynamic phase.

• Self-organizing and error remover system, the clusters and centroids are always valid.

摘要

•Introducing a new enhanced K-Means clustering algorithm for dynamic clustering.•Detecting the nodes with the potential of changing their clusters after each change.•Completely local calculations during the dynamic phase.•Self-organizing and error remover system, the clusters and centroids are always valid.

论文关键词：Clustering,Dynamic networks,K-means,Re-clustering

论文评审过程：Received 17 October 2018, Revised 5 March 2019, Accepted 27 April 2019, Available online 30 April 2019, Version of Record 10 May 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.04.061